3
NVIDIA DRIVE PX 212 CPU cores | Pascal GPU | 8 TFLOPS | 24 DL TOPS | 16nm FF | 250W | Liquid Cooled
World’s First AI Supercomputer for Self-Driving Cars
9
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2009 2010 2011 2012 2013 2014 2015 2016
THE AI RACE IS ON
IBM Watson Achieves Breakthrough in Natural Language Processing
Facebook Launches Big Sur
Baidu Deep Speech 2Beats Humans
Google Launches TensorFlow
Microsoft & U. Science & Tech, China Beat Humans on IQ
Toyota Invests $1B in AI Labs
IMAGENETAccuracy Rate
Traditional CV Deep Learning
10
EDUCATION
START-UPS
CNTKTENSORFLOW
DL4J
THE ENGINE OF MODERN AI
NVIDIA GPU PLATFORM
*U. Washington, CMU, Stanford, TuSimple, NYU, Microsoft, U. Alberta, MIT, NYU Shanghai
VITRUVIANSCHULTS
LABORATORIES
TORCH
THEANO
CAFFE
MATCONVNET
PURINEMOCHA.JL
MINERVA MXNET*
CHAINER
BIG SUR WATSON
OPENDEEPKERAS
12
END-TO-END DEEP LEARNING PLATFORMFOR SELF-DRIVING CARS
DNN TRAINING PLATFORM
IN-CAR AI SUPERCOMPUTER
DEEP NEURAL NETWORK
13
39%
55%
72%
88%
30%
40%
50%
60%
70%
80%
90%
100%
7/2015 8/2015 9/2015 10/2015 11/2015 12/2015
Top Score
9 inception layers
3 convolutional layers
37M neurons
40B operations
Single and multi-class detection
Segmentation
KITTI Dataset: Object DetectionNVIDIA DRIVENet
18
“Using NVIDIA DIGITS deep
learning platform, in less than
four hours we achieved over 96%
accuracy using Ruhr University
Bochum’s traffic sign database.
While others invested years of
development to achieve similar
levels of perception with
classical computer vision
algorithms, we have been able
to do it at the speed of light.”
Matthias Rudolph, Director of Architecture,
Driver Assistance Systems, Audi
19
“Due to deep learning,
we brought the vehicle’s
environment perception a
significant step closer to human
performance and exceeded the
performance of classic computer
vision.”
Ralf G. Herrtwich
Director of Vehicle Automation, Daimler
20
Image from ZMP
[Sahin]
“Deep learning technology can
dramatically improve accuracy
of detection and decision-
making algorithms for
autonomous driving. ZMP is
achieving remarkable results
using deep neural networks on
NVIDIA GPUs for pedestrian
detection. We will expand our
use of deep learning on NVIDIA
GPUs to realize our driverless
Robot Taxi service.”
Hisashi Taniguchi
CEO, ZMP Inc.
21
“BMW is exploring the use of
deep learning for a wide range
of automotive use cases, from
autonomous driving to quality
inspection in manufacturing.
The ability to rapidly train deep
neural networks on vast amounts
of data is critical. Using an NVIDIA
GPU cluster with NVIDIA DIGITS,
we are achieving excellent results.”
Uwe Higgen
Head of BMW Group Technology Office (USA)
22
“With the NVIDIA deep learning
platform, we have greatly
improved performance on a variety
of image recognition applications
for cars, surveillance cameras and
robotics. The remarkable thing is
that we did it all with a single
NVIDIA GPU-powered deep neural
network, in a very short time.”
Daisuke Okanohara
Founder & SVP, Preferred Networks
Distributed Cooperative Deep Learning
23
“Deep learning on NVIDIA DIGITS
has allowed for a 30x enhancement
in training pedestrian detection
algorithms, which are being
further tested and developed as
we move them onto the NVIDIA
DRIVE PX.”
Dragos Maciuca, Technical Director,
Ford Research and Innovation Center
25
END-TO-END DEEP LEARNING PLATFORMFOR SELF-DRIVING CARS
NVIDIA DRIVE PX 2NVIDIA DIGITS
NVIDIA DRIVENET
Localization
Planning
Visualization
Perception
DRIVEWORKS
28
NVIDIA DRIVE PX 2TITAN X DRIVE PX 2
Process 28nm 16nm FinFET
CPU —
12 CPU cores
8-core A57 +
4-core Denver
GPU Maxwell Pascal
TFLOPS 7 8
DL TOPS 7 24
AlexNet 450 images / sec 2,800 images / sec
29
150 MACBOOK PROS IN YOUR TRUNK
6 TITAN X = 42 TFLOPS, Core i7 = 280 GFLOPS, 42 / 0.28 = 150 MacBook Pros
35
NVIDIA DRIVE PXSELF-DRIVING CAR PLATFORM
NVIDIA DRIVE PX 2NVIDIA DIGITS
NVIDIA DRIVENET
Localization
Planning
Visualization
Perception
DRIVEWORKS